.png){kind=icon}
.png){kind=icon}
Return
Multi-loop nonlinear internal model controller design based on a dynamic fuzzy partial least squares model
.png){kind=icon}
PRE
AI
DOI：10.1016/j.cherd.2013.04.019.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
In this paper, a dynamic fuzzy partial least squares (DFPLS) modeling method is proposed. Under such framework, the multiple input multiple output (MIMO) nonlinear system can be automatically decomposed into several univariate subsystems in PLS latent space. Within each latent space, a dynamic fuzzy method is introduced to model the inherent dynamic and nonlinear feature of the physical system. The new modeling method combines the decoupling characteristic of PLS framework and the ability of dynamic nonlinear modeling in the fuzzy method. Based on the DFPLS model, a multi-loop nonlinear internal model control (IMC) strategy is proposed. A pH neutralization process and a methylcyclohexane (MCH) distillation column from Aspen Dynamic Module are presented to demonstrate the effectiveness of the proposed modeling method and control strategy. (C) 2013 The Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.
Keywords:
Partial least squares
TSK fuzzy model
Internal model control
pH neutralization
MCH distillation column
Journal
IF:
3.9
Papers:
9.0K
Citations:
2.1W